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20232026
most citedTranscription-Free Fine-Tuning of Speech Separation Models for Noisy and Reverberant Multi-Speaker Automatic Speech Recognition

1 citations · 1 across the 10 of their papers we have counts for

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cs.SD2023

Multi-CMGAN+/+: Leveraging Multi-Objective Speech Quality Metric Prediction for Speech Enhancement

George Close, William Ravenscroft, Thomas Hain +1

Neural network based approaches to speech enhancement have shown to be particularly powerful, being able to leverage a data-driven approach to result in a significant performance g…

cs.SD2023

On Time Domain Conformer Models for Monaural Speech Separation in Noisy Reverberant Acoustic Environments

William Ravenscroft, Stefan Goetze, Thomas Hain

Speech separation remains an important topic for multi-speaker technology researchers. Convolution augmented transformers (conformers) have performed well for many speech processin…